Content uploaded by Vilma Mattila
Author content
All content in this area was uploaded by Vilma Mattila on Apr 20, 2022
Content may be subject to copyright.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 264
HOMOMORPHIC ENCRYPTION IN 5IRE BLOCKCHAIN
VILMA MATTILA, PRATEEK DWIVEDI, PRATIK GAURI & MD AHBAB
5ire (Sustainable Distributed Computing) 160 City Rd, London,
United Kingdom
https://doi.org/10.37602/IJSSMR.2022.5219
ABSTRACT
With the advent of blockchain technology, decentralized system is gaining huge popularity as
it provides a new solution for data storage and sharing as well as keeping privacy in place.
Blockchains are of two categories; public and private. Public blockchains are permissionless,
mostly used for exchanging and mining cryptocurrency, where anyone can join and thus
exposed to the risk of a privacy breach. If the content is the transaction information, one
might opt for not sharing these data in the public domain. One solution could be to encrypt
the information, but that comes at the cost of losing the usability of the data. This paper in-
vestigates the security problem related to this passive adversarial activity and proposes a new
technology that leverages the best parallel chain architecture of 5ire blockchain and
homomorphic encryption (HE) so as to retain the advantages of a public blockchain without
compromising the privacy of transaction information. We have coined the term 5ireHE for
this encryption architecture. We achieve the security protection and integrity check of wallet
data by enforcing the 5ireHE which is efficient.
1.0 INTRODUCTION
With the advent of Blockchain technology, a decentralized system is a reality that provides a
new solution for data storage and sharing while keeping privacy in place. Publicly available
data can be secured by encrypting, however, this re- dux the usability of the data in a sense
that unless decrypted, no operation can be performed on the encrypted data. Towards this, the
idea of homomorphic encryption has been conceptualized where certain operations are
possible on the encrypted data directly without having to decrypt it. When combined with
blockchain, these features of homomorphic encryption could lead to a new platform of agile
and yet highly resilient secure computing strategies. Although the idea of homomorphic
encryption was introduced in 1978, however, the first fully homomorphic encryption scheme,
in short, FHE, was becoming a reality following the phenomenal work done by Gentry et al
[5]. The goal of homomorphic encryption is to allow an infinite number of additions or
multiplications of encrypted data with the target of having the ciphertext that would be
produced, had the same operations been performed on the corresponding plaintexts. The
problem is that designing such an encryption algorithm is really hard. As a result, there are a
few different “types” of homomorphic encryption that describe how close a particular
algorithm is to that final goal. Despite being an ideal solution for solving a variety of major
business challenges, there is no commercial use of FHE so far. One major problem with FHE
is that it is not efficient. Depending on the degree of freedom in terms of achieving full
functionality over the ciphertext domain, there are three categories of homomorphic
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 265
encryption; fully homomorphic encryption, somewhat homomorphic encryption, and partially
homomorphic encryption.
From the pool information in 5irechain, the sender’s identity can be derived publicly which is
acceptable, and also this is the basic assumption of 5irechain. However, we note that if the
amount of the transaction appears in plain text, then that may raise privacy concerns for both
the sender and receiver. Encrypt- in the amount will come at the cost of losing the usability of
the data in the blockchain. Suppose Alice is sending money to Bob. From the transaction
block information, conventionally which is kept in the form of plain text, it is possible for a
passive adversary to learn this transaction. It can be further observed that such an adversary
can extract a fair amount of wallet information of Alice by tracking all the inflow and outflow
of money corresponding to Alice’s ac- count by noting all transactions involving Alice.
Similarly, Bob and others' wallet information can be extracted.
5ireHE. Figure 3 represents the HE architecture in the 5ire blockchain. We coined the term
5ireHE for this. Let Alice wants to pay Bob and she creates a transaction block for this in a
transaction pool which is determined by the hash value of Alice’s transaction public key.
Unlike traditional block creation, here Alice uses Bob’s public key for Homomorphic
Encryption to encrypt the amount while creating the block. This block is then broadcasted to
all members in the 5ire blockchain corresponding to that transaction pool for validation. Once
it is verified, according to 5ire architecture, it is added to the 5ire block and the money moves
to Bob’s wallet in an encrypted form. Bob can vary the amount of decryption and can
perform the aggregate operations of all credited amounts directly on the encrypted wallet
information.
This paper proposes a new technology that leverages the best parallel chain archetecture of
5ire blockchain and homomorphic encryption (HE). We achieve the security protection and
integrity check of wallet data by enforcing HE which is efficient. On the one hand, HE is an
efficient solution for privacy-preserving wallet computation but on the other hand, HE is
susceptible to IND-CC2 attack. We introduce a second layer of authentication so as to
provide safeguards against such attacks. On the one hand, homomorphic encryption is an
efficient solution for privacy-preserving wallet computation but on the other hand, it is
susceptible to IND-CC2 attack. It is to be noted that the IND-CC2 attack assumes access to
the decryption oracle. However, we observe that since the 5ireHE architecture enforces each
individual to generate the 5ireHE key pair and that the transaction to be encrypted by the
public key of the receiver for which the corresponding private key is to be kept solely by the
receiver, IND-CPA security of transaction will suffice to assert the transaction security in
5ireHE. We introduce a second layer of authentication so as to provide safeguards against
such attacks.
2.0 RELATED WORK
With the growing popularity of blockchain, several research works have been conducted to
explore privacy in the context of blockchain [1–4, 6–8, 10]. Rather than customized
solutions for specific use cases, we here focus on the privacy of transaction data from passive
adversaries.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 266
Since a blockchain-based IoT network is public, so transactional details and encrypted keys
are exposed to everybody in that network. Thus, anybody in the network can infer critical
information of users from this public infrastructure. In [6] authors discussed the privacy
issues caused due to the integration of blockchain in IoT applications. The work in [8]
evaluates blockchain’s roles in strengthening- ing cybersecurity and protecting privacy.
Owing to the majority of data being stored in the cloud, the authors also provided a
comparison as to how blockchain per- forms vis-vis the cloud in various aspects of security
and privacy. In [3] authors proposed a blockchain-based model for data storage and addressed
the problem of data synchronization. To improve the performance of users’ workstations,
they designed the DEPLEST method to be embedded in the front of the existing database to
capture sensitive data. They also implemented a stochastic homo- morphic elliptic curve
cryptography (SHECC) encryption model to improve data security and efficiency. In [7], a
private smart contract called HAWK was proposed which is based on ZKPs. Hawk assumed
a semi-trusted manager, who is trusted with protecting the privacy of the users’ inputs but not
for the correctness of computation. In [4] Ekiden was proposed which relies on trusted
hardware rather than a trusted manager. Following this, research has been conducted to avoid
trusted parties or hardware. In [2] Zether was proposed which targeted smart contract privacy
for Ethereum. Its reliance on additively homomorphic encryption restricts its functionality to
private currency transfer and a limited class of private smart contracts. The authors noted that
though Zether upholds anonymity, this feature cannot be implemented on Ethereum as the
cost will exceed the gas limit per block. Okay [10] proposed a compiler for private smart
contracts. Okay follows the pure ZKP approach by overloading end users and depends on off-
chain coordination to handle multi-user inputs. Sexe in [1] enhanced privacy further by also
preserving function privacy. Following the pure ZKP approach, Zexe operates in the UTXO-
based model which attempted to limit the supported functionality to extending Zerocash
scripts used to spend currency.
3.0 PROBLEM DEFINITION
In the 5ire chain, the issue of scalability is addressed by maintaining parallel chains. To
uphold this, the 5ire chain allows multiple transaction pools, one for each parallel chain.
Whenever the number of transactions in a transaction pool surpasses a threshold, that
particular transaction pool is divided into two different pools. For this purpose, we make use
of hash functions. A transaction goes into one of the pools depending upon the hash value of
the public key of the transaction-sender. Roughly speaking, if there are n transaction pools,
each pool is dynamically assigned a number which is a bit-string of size at most logn. Thus
from the pool of information, the sender’s identity can be derived publicly, however, if the
amount of the transaction appears in plain text, then that may raise the privacy concern for
both the sender and receiver. Encrypting the amount will come at the cost of losing the
usability of the data in the blockchain.
4.0 OVERVIEW OF THE SCHEME
4.1 System Overview
5ire introduces the nested blockchain where nodes can create concurrent blocks and maintain
smaller chains, which can later be merged into 5irechain. Thus, instead of having a linear
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 267
blockchain 5irechain can be view upon as to be a tree-structured blockchain followed by a
5ire block, which will nest the smaller chains together. In order to process the transactions at
scale, it is crucial for nodes from autonomous groups to be able to concurrently process
transactions and form their own chains. Nested-Chains in 5irechain addresses this issue of
scalability by maintaining the parallel chains. These chains are created on a need basis
depending on the load on the network. However, once a chain is created it will continue
adding blocks until the chain is joined with the 5irechain using a 5ire block. Figure 1 shows
the structure of the nested chain. The nested chains not only support the scalability in the
blockchain but also enables us to support the creation of parallel chains without adding new
nodes (Assemblers, Attesters/voters, ESG Experts). This essentially means that nodes will be
running- in multiple parallel chains on a single node, but as a separate process. 5ire will use
the scheduling algorithms to make sure the maximum utilization of the nodes. Therefore,
unlike the conventional blockchains where nodes will sit idle and wait for their turn to create
the block, the nodes in the 5ire ecosystem may get turns to create blocks into another parallel
chain in the nested chain. The nodes in all the parallel chains will be selected in a similar way
i.e. based on their weights (Reliability Score, Stake, ESG score, and Randomized voting).
4.2 Threat Model
Suppose Alice is sending money to Bob. From the transaction block information,
conventionally which is kept in the form of plain text, it is possible for a passive adversary to
learn this transaction. It can be further observed that such an adversary can extract a fair
amount of wallet information of Alice by tracking all the inflow and outflow of money
corresponding to Alice’s account by noting all transactions involving Alice. Similarly, Bob
and others' wallet information can be extracted.
4.3 Privacy Protection within 5ireChain Homomorphic Encryption
The blockchain is composed of multiple blocks and each node in the 5ireChain network
stores the same blockchain. The emanate block includes the blockhead and the block body.
Fig. 1: 5ire Nested Chain
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 268
Where the Block Body contains information stored as meta-data, and the Block Head holds
the input metadata information like version, timestamp, characteristic value, difficulty value,
etc. The next block of the emanate block is known as the parent block, and the proceeding
next block also includes the blockhead and the block body, so each block is in the blockchain
filled with a similar set of information. The block data stored in the block is associated with
the block data stored in the parent block, which ensures the security of the input information
in the block. The steps of this algorithm are as follows.
Step 1: Key Generation: Initialize random primes p and q and meet the condition of: gcd(PQ,
(p − 1)(q − 1)) = 1
Module calculation n = pq, λ = lcm(p−1, q−1), where lcm is to seek the least common
multiple of p −1 and q −1. Select the random number g ∈ Z∗n2 and meet µ = L g mod n
mod n the greatest common divisor of L g mod n and n Zn∗ 2 represents the set of integers
coprime to n2 Zn2. The public key for encryption is (n, g) and the private key is (λ, µ). Select
integer in encryption and decryption process, r(r ∈ Zn2 ), and the plaintext is m(m ∈ Zn) and
m < n.
Step 2: (encryption→− Enc(m, pk)): Let m be the information to be encrypted and m ∈
Zn. Compute the ciphertext: c from m mod n. The encryption process is c = E(m) = gm · rn
mod n2.
where c is the ciphertext data corresponding to the plaintext m and c Z∗n2. Mark the
encryption algorithm as c=E(m, r). It may be noted that for the same ciphertext m, the value
of r, which is randomly selected in the encryption process may be different and so is the
corresponding ciphertext data c. This property ensures the semantic security of ciphertext
data.
Step 3: (proxy re-encryption): Compute the public key and private key (Rsk, Rpk).
The re-encryption ciphertext is generated by the RSA algorithm, and the public key Rpk is
sent to the server.
Step 4: (decryption→− Dec(c, sk)): Here the ciphertext c ∈ Z∗n2 for which following is
computed: m = Dec(c, sk) = L(cλ mod n2) · µ mod n
4.4 Overview of HE architecture in 5ire blockchain
Figure 2 represents the HE architecture in the 5ire blockchain. Let Alice wants to pay Bob
and she creates a transaction block for this in a transaction pool which is determined by the
hash value of Alice’s transaction public key. Unlike traditional block creation, here Alice
uses Bob’s public key for Homomorphic Encryption to encrypt the amount while creating the
block. This block is then broadcasted to all members in the 5ire blockchain corresponding to
that transaction pool for validation. Once it is verified, according to 5ire architecture, it is
added to the 5ire block and the money moves to Bob’s wallet in an encrypted form. Bob can
vary the amount of decryption and can perform the aggregate operation of the all credited
amount directly on the encrypted wallet information.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 269
Fig. 2: Secure Transaction data computing in 5ire nested chain architecture using
Homomorphic Encryption
5.0 THE SCHEME
5.1 Cryptographic tools
Pseudo-Random Prime number Generator(PRNG). PRNG takes as input security parameter
1γ and outputs γ bit long prime numbers. Since this is a probabilistic algorithm, we denote it
as p ←−$ PRNG (1γ).
Paillier encryption. This public key cryptosystem has three algorithms, namely KeyGen,
Encryption, and Decryption.
– KeyGen(γ) : Choose two γ-bit prime numbers p and q randomly and independently of
each other such that gcd(pq, (p 1)(q 1)) = 1. This prop- party is assured if both primes
are of equal length. Compute n = pq and λ = lcm(p 1, q 1). Select random
integer g where g n∗2 . Ensure n divides the order of g by checking the
existence of the following modular multiplicative inverse: µ = (L(gλ mod n2))−1mod
n, where function L is defined as L(x) = x−1. Finally set pk = (n, g) and sk = (λ, µ)
– Encryption(m, pk) : Let m be a message to be encrypted where 0 < m < n. Select
random 0 < r < n. Compute ciphertext as c = gm · rn mod n2.
– Decryption(m, pk): Let c be the ciphertext to decrypt, where c ∈ Z∗n2. Compute
the plaintext message as: m = L(cλ mod n2) · µ mod n.
5ire Block Structure. A standard 5ire block is composed of a header and a body, where a
header contains the hash of the previous block, a timestamp, Nonce, and the Merkle root. The
Merkle root is the root hash of a Merkle tree which is stored in the block body.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 270
Fig. 3: 5ire Block Structure
We denote a 5ire block as =, where is parsed as = h, t, no, m, where h is a previous hash,
t is the timestamp, no is the bounce and m is the Markle root. The body of the block is parsed
as = sid, rid, a, where sid is the sender’s ID, rid is the receiver’s ID and a is the amount
being sent.
5.2 5ireHE protocol
The HM5ire scheme is applied on top of a public smart contract-enabled nested 5irechain. It
can be viewed as the mechanism needed to support privacy-preserving transactions from
passive adversaries.
Here we present the 5ireHE scheme which focuses on the new modules needed to support
privacy-preserving transactions where the receiver can directly operate on the encrypted
wallet encryption.
5ireHE is a tuple of PPT algorithms which is presented as 5ireHE = (KeyGen, Encrypt,
Decrypt, Encrypt5ireWallet, Decrypt5ireWallet). In the following figures, we present these
algorithms.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 271
5.3 Security of the 5ireHE protocol
A passive adversary in 5ireHE is one who can passively see all the 5ire transactions and takes
no actions in beyond recording the transactions and attempting to learn about the plaintext of
documents. We introduce the notion of Transaction Indistinguishability to model the possible
attacks and prove that 5ireHE is secure against such attacks.
Transaction Indistinguishability. Transaction indistinguishability ensures that the ledger
produced by the 5ireHE protocol does not reveal additional information about transaction
data beyond what can be inferred from what is publicly revealed. We define a Transaction-
Indistinguishability-Game to capture this.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 272
Definition 1. (Transaction Indistinguishability). An encrypted transaction in the blockchain
satisfy transaction indistinguishability, or TI in short, if for all PPT adversaries A, AdvT I (γ)
< negl(γ). We call such protocol TI-secure.
Exp
T
I
(γ)
A
(pk = (g, n), sk = (µ, λ) ← KeyGen(1
γ
)
Encrypt(pk,·)
(tx
0
, tx
1
, st) ← A
0
$
d
←
−
{
0
,
1
}
c ← Encrypt(pk, tx
d
)
Encrypt(pk,·)
d
′
← A
1
(c, st)
Return (d
=
d
′
)
/* tx
0
and tx
1
are distinct with different amount. */
/* A
0
, and A
1
cannot make a Encrypt(pk, ·) query on
an amount
that belongs to either tx
0
or tx
1
, but not
both. */
Before going into the proof, we introduce Decisional Composite Residuosity assumption
here.
Definition 2 (Decisional Composite Residuosity Assumption (DCS)).
[9] We say DCR is hard if for all PPT adversary B = (B0, B1),
AdvDCS(γ) ≤ negl(γ).
Theorem 1. 5ireHE protocol is TI-secure.
Proof. Let there exists a PPT adversary A = (A0, A1) such that AdvT I (γ) >
negl(γ). For such A, we show that a PPT adversary C
simulate the adversary C as follows :
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 273
1. C runs KeyGen(1γ) and sets pk = (g, n), sk = (µ, λ).
A can solve DCS. We
2. C runs A Encrypt (pk,·) to obtain tx0 and tx1 ans state st.
3. C runs B0(n) to obtain c0 = rn mod n2, and c1 ←−
Z∗n2
4. C selects b ←−$ {0, 1} and d ←−
{0, 1}
5. C sets c = gtxd · rb mod n2
6. C runs and gets d′ ←− AEncrypt(pk,·)(c, st)
7. if d = d′, C outputs 1 else it outputs 0.
It can be noted that when b = 0, A1 receives a proper 5ireHE cipher
c = gtxd .r0 mod n2 = gtxd .rn mod n2.
But when b = 1, from A1’s point of view, it is purely random over Z∗n2 as in this case as
r1 = r ←−$
Z∗n2 and c = gtxd .r1 mod n2 = gtxd .r mod n2
Thus ADVC(γ) = 1 AdvDCS(γ) ≥ AdvT I (γ) > negl(γ).
2 Clearly AdvDC ⊔⊓
5.4 Performance
In this section, we provide the performance results of our proposed scheme 5ireHE. We build
a 5ireHE using c++ on the Linux platform. The implementation is done on Asus A Series
Core i3 laptop ((4 GB/ 1 TB HDD) 90NB0652-M32310 XX2064D). We use C++ Library
‘libpaillier’ for the cryptographic primitives.
In Figure 4 we represent the transaction encryption and decryption timing using 5ireHE.
Along X-axis we plot transaction data presented in KB and along Y-axis we plot the timing
for the operation in milliseconds. In 4 (a) The performances of encryption in 5ireHE are
compared for two modes of implementations corresponding to two key sizes 512 bit and 1024
bit. For 1KB size of the transaction, 5ireHE encryption takes 8070 milliseconds with a 512-
bit key and 63062 milliseconds with a 1024-bit key. In Figure 4 (b) shows the decryption
performance for two different key sizes using 5ireHE decryption functionality. For 1KB size
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 274
of the transaction, 5ireHE decryption takes 17000 milliseconds with 512-bit key and 126209
milliseconds with a 1024-bit key.
(a) 5ireHE Encryption timing (b) 5ireHE Decryption timing
Fig. 4: 5ireHE Encryption and Decryption performance graph
The timing for computation is very less compared to the encryption and decryption timing.
With 512-bit key, the timing for multiplying 1 KB ciphertexts, is 71 milliseconds and that
with 1024-bit key is 180 milliseconds. For the scalar multiplications of 1KB transaction
cipher with a constant, 12, is 254 milliseconds and 645 milliseconds with 512-bit key and
1024-bit key respectively.
6.0 PRIVACY PROTECTION WITHIN 5IRECHAIN
The blockchain is composed of multiple blocks and each node in the 5ireChain network
stores the same blockchain. The emanate block includes the block head and the block body.
Where the Block Body contains information stored as meta- data, and the Block Head holds
the input metadata information like: version, timestamp, characteristic value, and difficulty
value, etc. The next block of the emanate block is known as the parent block, and proceeding
next block also includes the block head and the block body, so each block is in the blockchain
filled with a similar set of information. The block data stored in the block is associated with
the block data stored in the parent block, which ensures the security of the input information
in the block. The steps of this algorithm are as follows.
Step 1: Key Generation: Initialize random primes p and q and meet the condition of: gcd (pq,
(p-1)(q-1)) = 1
Module calculation n=pq. =1cm(p1,q1), where 1cm is to seek the least com- mon multiple of
p1 and q1 Select the random number g(g Z*n2) and meet = Lg mod n2-1 mod n The greatest
common divisor of L(g mod n2) and n. Zn2 represents the set of integers coprime to n2 in
Zn2. The encrypted public key of function Lx = x 1/n is n, g, and the private key is (, ). Select
integer in encryption and decryption process, r(r Zn22 ), and the plaintext is r(r Zn) and m ¡ n.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 275
Step 2: (encryptionEnc (m, pk): Let m be the information to be encrypted and m Zn.
Compute the ciphertext: c = m mod n. The encryption process is c=E(m) = gm .rn mod n2
Where c is the ciphertext data corresponding to the plaintext m and c Zn2*. Mark the
encryption algorithm as c=E(m, r). It can be known that for the same ciphertext m, the
value of r, which is randomly selected in the encryption process may be different and so is the
corresponding ciphertext data after being encrypted so as to ensure the semantic security of
ciphertext data.
Step 3: (proxy re-encryption): Compute the public key and private key (Rsk, Rpk).
The re-encryption ciphertext is generated by the RSA algorithm, and the public key Rpk is
sent to the server.
Step 4: (decryption Dec(c, sk)): Ciphertext c Zn m=D(c)=Lc mod n2* ( mod n)
After receiving E(di)(i p), decrypt it to get (di)(i p), sign it, get and send
Signq(di)(i p) to ENq. Step 5: (after ENq receives (di)(i p), divide the degree of dispersion
into two kinds). Make the set of users corresponding to the kind with more elements as Q and
the set of users corresponding to the degree of dispersion as G. As malicious users take up a
small proportion, Q mainly includes normal users with the target value increasing after the
completion of tasks, while that of G decreases after tasks end. Therefore, it has introduced
two parameters and to control the increase and decrease after the target value is updated, and
the target value changes according to the following equation: rinew= ri . (1-v)ri . (1-ri) . if i
Gif Q where and are both positive and ¡ 1.
7.0 CONCLUSION
In the public blockchain, the intigrity of data is maintained due to the security constructs of
blockchain. However this does not guarantee the safety against leakage of transaction data
due to passive advesarial presence. Encrypting the data using traditional encryption system
comes at the cost of loosing the usability of the data in a sence that unless decrypted the
owner can not use the data for future computation. Given the huge size of data, it is not
always feasible. In this paper we combine the best of homomorphic encryption and
blockchain and propose 5ireHE protocol to safeguard the transaction data in 5irechain, which
is a public blockchain. This results can be generalized for any public blockchain.
REFERENCES
Sean Bowe, Alessandro Chiesa, Matthew Green, Ian Miers, Pratyush Mishra, and Howard
Wu. Zexe: Enabling decentralized private computation. In 2020 IEEE Symposium on
Security and Privacy (SP), pages 947–964. IEEE, 2020.
Benedikt Bu¨nz, Shashank Agrawal, Mahdi Zamani, and Dan Boneh. Zether: To-
wards privacy in a smart contract world. In International Conference on Financial
Cryptography and Data Security, pages 423–443. Springer, 2020.
International Journal of Social Sciences and Management Review
Volume: 05, Issue: 02 “ March - April 2022”
ISSN 2582-0176
www.ijssmr.org Copyright © IJSSMR 2022, All right reserved Page 276
Yun Chen, Hui Xie, Kun Lv, Shengjun Wei, and Changzhen Hu. Deplest: A blockchain-
based privacy-preserving distributed database toward user behaviors in social
networks. Information Sciences, 501:100–117, 2019.
Raymond Cheng, Fan Zhang, Jernej Kos, Warren He, Nicholas Hynes, Noah Johnson, Ari
Juels, Andrew Miller, and Dawn Song. Ekiden: A platform for confidentiality-
preserving, trustworthy, and performant smart contracts. In 2019 IEEE European
Symposium on Security and Privacy (EuroS&P), pages 185–200. IEEE, 2019.
Craig Gentry. A fully homomorphic encryption scheme. Stanford University, 2009.
Muneeb Ul Hassan, Mubashir Husain Rehmani, and Jinjun Chen. Privacy preservation in
blockchain-based iot systems: Integration issues, prospects, challenges, and future
research directions. Future Generation Computer Systems, 97:512–529, 2019.
Ahmed Kosba, Andrew Miller, Elaine Shi, Zikai Wen, and Charalampos Papaman- thou.
Hawk: The blockchain model of cryptography and privacy-preserving smart contracts.
In 2016 IEEE symposium on security and privacy (SP), pages 839–858. IEEE, 2016.
Nir Kshetri. Blockchain’s roles in strengthening cybersecurity and protecting pri- vacy.
Telecommunications policy, 41(10):1027–1038, 2017.
